Vertical Growth of Two-Dimensional Zinc Oxide Nanostructures on ITO-Coated Glass: Effects of Deposition Temperature and Deposition Time
Bibliographic record
Abstract
Two-dimensional (2D) zinc oxide (ZnO) nanostructures of thickness 40−100 nm and length up to several micrometers are vertically grown on indium−tin oxide-coated glass substrates by using electrochemical deposition in the temperature range of 22−90 °C. The deposition temperature is found to play a significant role in controlling the morphology of the nanostructures, from randomly oriented, poorly crystalline nanosheets at 22 °C to well-aligned nanowalls with wurtzite structure at 70 °C. At 80 °C, nanowalls are found to merge with one another, and they become patchy fibrillar structures at 90 °C. An optical direct band gap of 3.3 eV is measured for all the samples deposited above 50 °C, while their transmittance varies from 40 to 75%, depending on their morphologies. X-ray photoelectron spectroscopy (XPS) shows that the ZnO nanostructures are covered by a Zn(OH) 2 overlayer, in good accord with the general growth model that involves Zn 2+ hydroxylation followed by dehydration to ZnO. Furthermore, our XPS data also reveals the presence of chlorine throughout the ZnO nanostructures, which verifies for the first time the 2D growth mechanism that involves Cl - capping of the (0001) plane of ZnO and thereby redirecting growth in the (101̄0) plane. Early growth of nanowalls at 70 °C arising from spherical nanoparticles to elongated nanobars is demonstrated by varying the deposition time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".